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I am trying out org mode for emacs… so I can track common server errors and bugs… I just thought… what if I could have my list of common problems/solutions searched and linked into the repl… so everytime an error happens, org mode or something can suggest the common fix?
dunno. if there's an issue with a known fix, I'd fix the issue or make it hard to fall into it. e.g. use
(I assume these are business-specific issues. else I'd simply use Eastwood)
this would probably save me hours per week from just looking up my own trouble tickets in my trello… that’s where I organize all my tickets.
here is a jira plugin for emacs… maybe I can find something that searches my bug tickets automatically anytime there is a repl error or command line error?
I am going to try the trello emacs minor mode… and let you know how this goes… I think this is the best idea I’ve had all month
"... computation may depend on cognitive activity and not the other way around. The kind of cognition in question, we propose, is that which only arises within and is integrally bound up with specific sociocultural normative practices." - https://www.academia.edu/30701477/The_Cognitive_Basis_of_Computation_Putting_Computation_In_Its_Place
I guess the take-away claim is that the abstractions we use to program computers are somewhat imaginary... heady stuff
I saw Daniel Dennett and David Chalmers give a talk on "Possible Minds" at Pioneer Works not too long ago and they basically treated CBC as so obviously true that it didn't even need to be mentioned.
IIUC, this paper argues against CBC... or rather, switches the Cs - a Cognitive Basis of Computation
Yeah, it seems like a more developed version of what this blog post refers to as "Sapience." This post basically argues that the semantic content of cognition incorporates context to a degree that's completely uncaptured by our existing computational models of cognition. Any formal test of intelligence flattens the context that natural intelligence thrives in and thus makes it impossible to measure. https://fexpr.blogspot.com/2018/02/sapience-and-non-sapience.html?m=1 Or, as Dennett said in that talk "intelligence is knowing what to do when you don't know what to do." He said we're very far away from making machines that satisfy that definition of intelligence.
re: "Possible Minds" I noticed the latest episode on Sam Harris' podcast is titled such. https://samharris.org/podcasts/153-possible-minds/ interviews with George Dyson, Alison Gopnik, and Stuart Russell
> Neither does the fact that people can compute ‘in their heads’, without engaging in overt manipulation of symbols, show that in such cases the brain computes. Even in these cases, it is the person that computes. The fact that computing relies on, and would not be possible without the occurrence of specific brain processes does not entail that those brain processes themselves are computations. :thinking_face: :thinking_face: I guess this makes sense by way of analogy to other ways of computing things. Using a pencil and paper to do long division definitely doesn't entail that the pencil and paper are dividing the numbers. Seems like a very anti-reductionist account of cognition is the consequence of this view.
Yeah, I haven't heard much news about how cognition is not based on spike trains flowing through neural circuits... Not calling that computation may be a semantic quibble.
But I'd agree that a Clojure interpreter, for instance, has two different descriptions - one is our sugary understanding of the concepts, the other is the actual silicon and electrons that are representing the analogous concepts
And you could call the sugary side of that coin "cognitive" if you accept all epistemic facts to be somewhat cognitive
I don't think it's just the sugary concepts though – the paper seems to argue that the output of programs and the purpose they're put to is also the determiner of cognitive content. A language interpreter has no meaning (cognitively) until it actually interprets symbols for some purpose.
to say something "determines the cognitive content" of something else is just an unwieldy way of saying something gives meaning to something else, I think
I mean, if we accept that "meaning" is a cognitive affair. Or if we accept that all subjective, experiential affairs are "cognitive" in some way, then you get to the same conclusion.
yeah I guess that's something that I was implicitly assuming. I have no idea what a non-cognitive account of meaning would look like.
Do you think it could be argued that, in a way, all life in the universe have some layers of semantic, whereas the molecules underneath them are pure syntax, without semantics?
Or, could we argue that non-living, non-end-directed affairs (pure accidental affairs of things unaffected by living things) also can have a kind of semantics?
depending on how you're defining "semantics" here, people definitely argue for that view: https://plato.stanford.edu/entries/panpsychism/
I don't think that identifying structure in reality is enough to assume that reality has semantics. Semantics are a feature of language and they relate to the fact that language is structured, but not all structured things have semantics (in my view).
yeah, I think it's consistent with the criticism of naturalistic accounts of computation given in the paper.
I feel like a mainstream language added support for commas in numbers in source code, e.g.
1,000 = 1000 but I can't think of which it would be
Do you like ocaml? I heard great things. But I didn't realize it is single threaded? No?
commas and periods are a mess anyhow, the Dutch put a comma between the integer and fraction parts and use a period for thousands
well an underscore hasn’t been assigned a role in natural language just yet, so its a relatively safe bet 😉
Anyone have a good book they can recommend for learning GPU/shader programming, specifically in the context of “general purpose” GPU programming?
in Java, a comma already has a syntactic meaning, so that was not an option
I just recently learned about Amdahl’s law from a friend. It helps calculate performance boosts from parallel programming.
Most shaders are coded for a graphics processing unit (GPU), though this is not a strict requirement. Shading languages are usually used to program the programmable GPU rendering pipeline, which has mostly superseded the fixed-function pipeline that allowed only common geometry transformation and pixel-shading functions; with shaders, customized effects can be used. The position, hue, saturation, brightness, and contrast of all pixels, vertices, or textures used to construct a final image can be altered on the fly, using algorithms defined in the shader, and can be modified by external variables or textures introduced by the program calling the shader.
A lot of the wording around the subject still stems from its graphical roots, but GPUs have evolved to be general purpose computational units.